# -*- coding: utf-8 -*-
from datetime import timedelta
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
# from jms_hi.dwd.tab.dwd_tab_barscan_arrival_base_hi import jms_dwd__dwd_tab_barscan_arrival_base_hi
# from jms_hi.dwd.tab.dwd_tab_barscan_unloading_base_hi import jms_dwd__dwd_tab_barscan_unloading_base_hi
# from jms_hi.dwd.tab.dwd_tab_barscan_send_base_hi import jms_dwd__dwd_tab_barscan_send_base_hi
# from jms_hi.dwd.tab.dwd_tab_barscan_loading_base_hi import jms_dwd__dwd_tab_barscan_loading_base_hi
# from jms_hi.ods.tms.yl_tmsnew_branch_shipment_stop_hi import jms_ods__yl_tmsnew_branch_shipment_stop_hi
# from jms_hi.dim.dim_network_whole_massage import jms_dim__dim_network_whole_massage
#from jms.dwd.dwd_warhouse.dwd_wide_unsign_summary_waybill_dt import jms_dwd__dwd_wide_unsign_summary_waybill_dt
from jms_hi.dwd.tab.dwd_tab_barscan_taking_base_hi import jms_dwd__dwd_tab_barscan_taking_base_hi
from jms_hi.dwd.dwd_tab_barscan_arrival_send_base_hi import jms_dwd__dwd_tab_barscan_arrival_send_base_hi
from airflow.exceptions import AirflowSkipException
import pendulum

cst = pendulum.timezone('Asia/Shanghai')


class HiSparksqlOperator(SparkSqlOperator):
    def pre_execute(self, context):
        day = cst.convert(context['ti'].execution_date) + timedelta(days=1)

        days_of_hours = ['07']

        if day.strftime('%H') not in days_of_hours:
            print(f'{day.strftime("%H")} not in {days_of_hours}, should skip')
            raise AirflowSkipException()
        else:
            print(f'{day.strftime("%H")} in {days_of_hours}, run now')
            super().pre_execute(context)


#jms_dwd__dwd_wide_unsign_summary_waybill_dt = WebHdfsSensor(
#    pool='unlimited_pool',
#    task_id="jms_dwd__dwd_wide_unsign_summary_waybill_dt_check_hdfs",
#    filepath='/dw/hive/jms_dwd.db/external/dwd_wide_unsign_summary_waybill_dt/dt={{ execution_date | cst_ds }}',
#    execution_timeout=timedelta(minutes=15),
#    email=['matthew.xiong@jtexpress.com', 'yl_bigdata@yl-scm.com'],
#    retries=2,
#)


jms_dm__dm_outport_effect_detail_dt = HiSparksqlOperator(
    task_id='jms_dm__dm_outport_effect_detail_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    execution_timeout=timedelta(minutes=30),
    email=['matthew.xiong@jtexpress.com', 'yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_outport_effect_detail_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms_hi/dm/dm_outport_effect_detail_dt/execute.hql',
    driver_memory='4G',
    executor_memory='5G',
    executor_cores=4,
    num_executors=10,
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled' : 'true',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors'  : 12,  # 动态资源最大扩容 Executor 数
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.sql.sources.partitionOverwriteMode' : 'dynamic',  # 允许删改已存在的分区
        'spark.executor.memoryOverhead'  : '2G',  # 堆外内存
        'spark.sql.shuffle.partitions'  : 100,
        'spark.default.parallelism'  : 100,
        'spark.sql.auto.repartition' :'true'
    },
    hiveconf={
        'hive.exec.dynamic.partition': 'true',
        'hive.exec.dynamic.partition.mode': 'nonstrict',
        'hive.exec.max.dynamic.partitions.pernode': 200,
        'hive.exec.max.dynamic.partitions': 200
    },
    yarn_queue='pro',
)

jms_dm__dm_outport_effect_detail_dt << [
    # jms_dwd__dwd_tab_barscan_arrival_base_hi,
    # jms_dwd__dwd_tab_barscan_unloading_base_hi,
    # jms_dwd__dwd_tab_barscan_send_base_hi,
    # jms_dwd__dwd_tab_barscan_loading_base_hi,
    # jms_ods__yl_tmsnew_branch_shipment_stop_hi,   #支线经停表
    # jms_dim__dim_network_whole_massage,           #网点维表
    #jms_dwd__dwd_wide_unsign_summary_waybill_dt,  #未签收宽表
    jms_dwd__dwd_tab_barscan_arrival_send_base_hi,
    jms_dwd__dwd_tab_barscan_taking_base_hi,
]



